Adaptive cloudiness index for enhanced photovoltaic energy prediction and management in low-income smart homes using geographic information system

Author:

Elazab Rasha,Saif Omar,Metwally Amr M. A. Amin,Daowd Mohamed

Abstract

AbstractSolar-powered homes can be an optimal solution for the lack of continuous power sources problem in initial low-income communities. However, the challenge of Photovoltaic (PV) uncertainty can make it difficult to coordinate this vital solar energy in real-time. This paper proposes a new, low-cost solution for assessing the uncertainty of photovoltaic power generation in smart home energy management systems. The proposed index, inspired by the well-known clearness index, is an adaptive deterministic indicator that only requires free Geographic Information System (GIS) models and PV power measurement, without the need for expensive high-tech controllers or expert engineers/programmers. The proposed index successfully predicts the daily PV energy with errors of less than 3% for more than 93% of studied days, according to the 2020 measured solar radiation of the studied case in an African developing location, i.e. Cairo. Egypt.

Funder

Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB).

Helwan University

Publisher

Springer Science and Business Media LLC

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